Path Planning of Mobile Robot Based on Hybrid Multi-Objective Bare Bones Particle Swarm Optimization With Differential Evolution

Abstract

An improved path planning for mobile robots is proposed based on the hybrid multi-objective bare-bones particle swarm optimization with differential evolution. The mathematical model for robot path planning is firstly devised as a tri-objective optimization with three indices, i.e., the path length, the smoothness degree of a path, and the safety degree of a path. Then, a hybrid multi-objective bare bones particle swarm optimization is developed to generate feasible paths by combining infeasible paths blocked by obstacles with feasible paths via improved mutation strategies of differential evolution. In addition, a new Pareto domination with collision constraints is developed to select the personal best position of a particle according to the definition of the collision degree of a path. Simulation results confirm the effectiveness of our algorithm.